/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

syntax = "proto2";

package tflite.evaluation;

import "tensorflow/lite/tools/evaluation/proto/evaluation_stages.proto";

// Contains parameters that define how an EvaluationStage will be executed.
// This would typically be validated only once during initialization, so should
// not contain any variables that change with each run.
//
// Next ID: 3
message EvaluationStageConfig {
  optional string name = 1;

  // Specification defining what this stage does, and any required parameters.
  optional ProcessSpecification specification = 2;
}

// Metrics returned from EvaluationStage.LatestMetrics() need not have all
// fields set.
message EvaluationStageMetrics {
  // Total number of times the EvaluationStage is run.
  optional int32 num_runs = 1;

  // Process-specific numbers such as latencies, accuracy, etc.
  optional ProcessMetrics process_metrics = 2;
}
